Bagging survival trees

Statistics in Medicine

Volumn 23, Issue 1, 2004, Pages 77-91

  Hothorn, Torsten ^a   Lausen, Berthold ^a   Benner, Axel ^b   Radespiel Tröger, Martin ^c  

^a UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

^b GERMAN CANCER RESEARCH CENTER DKFZ   (Germany)

^c Population Based Cancer Registry Bavaria   (Germany)

Author keywords

Bootstrap aggregation; Brier score; Censored data; Prognostic factors

Indexed keywords

DNA;

ADULT; ANALYTIC METHOD; ARTICLE; B CELL LYMPHOMA; BREAST CANCER; CANCER SURVIVAL; CONTROLLED STUDY; DATA ANALYSIS; DNA MICROARRAY; EXPERIMENTAL DESIGN; GERMANY; HUMAN; KAPLAN MEIER METHOD; MATHEMATICAL COMPUTING; OBSERVATION; PILOT STUDY; PREDICTION; PROGNOSIS; SCORING SYSTEM; SIMULATION; STATISTICAL MODEL; SURVIVAL RATE;

BREAST NEOPLASMS; CLINICAL TRIALS; FEMALE; GERMANY; HUMANS; LYMPHOMA; MALE; MODELS, STATISTICAL; SURVIVAL ANALYSIS;

EID: 0346656880     PISSN: 02776715     EISSN: None     Source Type: Journal    
DOI: 10.1002/sim.1593     Document Type: Article

References (37)

1. Schumacher M, Holländer N, Schwarzer G, Sauerbrei W. Prognostic factor studies. In Statistics in Oncology, Crowley J (ed.). Marcel Dekker: New York, Basel, 2001; 321-378.
2. Graf E, Schmoor C, Sauerbrei W, Schumacher M. Assessment and comparison of prognostic classification schemes for survival data. Statistics in Medicine 1999; 18:2529-2545.
3. LeBlane M. Tree-based methods for prognostic stratification. In Statistics in Oncology, Crowley J (ed.). Marcel Dekker: New York, Basel, 2001; 457-472.
4. Gordon L, Olshen R. Tree-structured survival analysis. Cancer Treatment Reports 1985; 69:1065-1069.
5. Ciampi A, Chang C, Hogg S, McKinney S. Recursive partition: a versatile method for exploratory data analysis in biostatistics. In Proceedings from Joshi Festschrift, Umphrey G (ed). North-Holland: Amsterdam, 1987; 23-50.
6. Segal MR. Regression trees for censored data. Biometrics 1988; 44:35-47.
7. Davis RB, Anderson JR. Exponential survival trees. Statistics in Medicine 1989; 8:947-961.
8. LeBlanc M, Crowley J. Relative risk trees for censored survival data. Biometrics 1992; 48:411-425.
9. LeBlanc M, Crowley J. Survival trees by goodness of split. Journal of the American Statistical Association 1993; 88:457-467.
10. Keleş S, Segal MR. Residual-based tree-structured survival analysis. Statistics in Medicine 2002; 21:213-326.
11. Lausen B, Sauerbrei W, Schumacher M. Classification and regression trees (CART) used for the exploration of prognostic factors measured on different scales. In Computational Statistics, Dirschedl P, Ostermann R (eds). Physica-Verlag: Heidelberg, 1994; 483-496.
12. Lausen B, Schumacher M. Maximally selected rank statistics. Biometrics 1992; 48:73-85.
13. Kim H, Loh WY. Classification trees with unbiased multiway splits. Journal of the American Statistical Association 2001; 96:589-604.
14. Breiman L. Bagging predictors. Machine Learning 1996; 24:123-140.
15. Breiman L. Arcing classifiers. The Annals of Statistics 1998; 26:801-824.
16. Efron B. Censored data and the bootstrap. Journal of the American Statistical Association 1981: 76:312-319.
17. Akritas MG. Bootstrapping the Kaplan-Meier estimator. Journal of American Statistical Association 1986; 81:1032-1038.
18. Sauerbrei W. Bootstrapping in survival analysis. In Encyclopedia of Biostatistics, Armitage P, Colton T (eds). Wiley: Chichester, New York, 1998; 433-436.
19. Dannegger F. Tree stability diagnostics and some remedies for instability. Statistics in Medicine 2000; 19: 475-491.
20. Schumacher M, Basert G, Bojar H, Hübner K, Olschewski M, Sauerbrei W, Schmoor C, Beyerle C, Neumann RLA, Rauschecker HF for the German breast cancer study group. Randomized 2 × 2 trial evaluating hormonal treatment and the duration of chemotherapy in node-positive breast cancer patients. Journal of Clinical Oncology 1994; 12:2086-2093.
21. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X, Powell JI, Yang L, Marti GE, Moore T, Hudson J, Lu L, Lewis DB, Tibshirani R, Sherlock G, Chan WC, Greiner TC, Weisenburger DD, Armitage JO, Warnke R, Levy R, Wilson W, Grever MR, Byrd JC, Botstein D, Brown PO, Staudt LM. Distinct types of diffuse large B-cell lymphoma identified by expression profiling. Nature 2000; 403:503-511.
22. Henderson R. Problems and prediction in survival-data analysis. Statistics in Medicine 1995; 14:161-184.
23. Brier GW. Verification of forecasts expressed in terms of probability. Monthly Weather Review 1950; 78:1-3.
24. Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 1958; 53:457-481.
25. Breiman L, Friedman JH, Olshen RA, Stone CJ. Classification and Regression Trees. Wadsworth: California, 1984.
26. Bühlmann P, Yu B. Analyzing bagging. The Annals of Statistics 2002; 30:927-961.
27. Korn EL, Simon R. Measures of explained variation for survival data. Statistics in Medicine 1990; 9:487-503.
28. Altman DG, Royston P. What do we mean by validating a prognostic model? Statistics in Medicine 2000; 19:453-473.
29. Therneau T, Atkinson E. An introduction to recursive partitioning using the rpart routine. Technical Report 61, Section of Biostatistics, Mayo Clinic, Rochester, 1997.
30. Ihaka R, Gentleman R. R: A language for data analysis and graphics. Journal of Computational and Graphical Statistics 1996; 5:299-314.
31. Sauerbrei W, Royston P. Building multivariable prognostic and diagnostic models: transformation of the predictors by using fractional polynomials. Journal of the Royal Statistical Society, Series A 1999; 162: 71-94.
32. Eisen M. ScanAlyse User Manual. Stanford University: Stanford, CA, U.S.A., 1998.
33. Eisen M, Spellman P, Brown P, Botstein D. Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Science 1998; 95:14 863-14 868.
34. Dudoit S, Fridlyand J, Speed TP. Comparison of discrimination methods for the classification of tumours using gene expression data. Journal of the American Statistical Association 2002; 97:77-87.
35. Breiman L. Random forests. Machine Learning 2001; 45:5-32.
36. Friedman JH. Greedy function approximation: a gradient boosting machine. The Annals of Statistics 2001; 29:1189-1202.
37. Peters A, Hothorn T, Lausen B. ipred: improved predictors. R News 2002; 2:33-36 (ISSN 1609-3631).